old_linearrecogniser.h

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00001 /*  -*- c++ -*-  (for Emacs)
00002  *
00003  *  linearrecogniser.h
00004  *  Digest
00005  * 
00006  *  Created by Aidan Lane on Mon Jul 11 2005.
00007  *  Copyright (c) 2005 Optimisation and Constraint Solving Group,
00008  *  Monash University. All rights reserved.
00009  *
00010  *  This program is free software; you can redistribute it and/or modify
00011  *  it under the terms of the GNU General Public License as published by
00012  *  the Free Software Foundation; either version 2 of the License, or
00013  *  (at your option) any later version.
00014  *
00015  *  This program is distributed in the hope that it will be useful,
00016  *  but WITHOUT ANY WARRANTY; without even the implied warranty of
00017  *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
00018  *  GNU General Public License for more details.
00019  *
00020  *  You should have received a copy of the GNU General Public License
00021  *  along with this program; if not, write to the Free Software
00022  *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
00023  */
00024 
00025 #ifndef LINEARRECOGNISER_H
00026 #define LINEARRECOGNISER_H 
00027 
00028 
00029 #include "abstractrecogniser.h"
00030 
00031 
00032 #include <QHash>
00033 #include <QVector>
00034 
00035 class AbstractFeature;
00036 
00037 
00038 class LinearRecogniser : public AbstractRecogniser {
00039 
00040   typedef double WeightT; // TODO: share this with AbstractRecogniserTrainer
00041 
00042 public:
00043   LinearRecogniser( JavaVM* jvm );
00044 
00045   DECLARE_CLASS_KEY( "linear" );
00046   DECLARE_CLASS_TITLE( "Linear Recogniser" );
00047   DECLARE_CLASS_DESCRIPTION( "<B>Simple Linear Recogniser</B><BR><BR>"
00048                             "Although it requires 2 or more features to work, "
00049                             "there are no restrictions on which features can or "
00050                             "cannot be used." );
00051 
00052 
00053 protected:
00054   bool readModelFile( const QString& fileName );
00055 
00056   ClassProbabilities classifyGestureImp( const DGestureRecord& gesture,
00057                                      const QVector<FeatureResultT>& featureVec );
00058 
00059 
00060 private:
00061   QHash< int, QVector<WeightT> > m_classWeights;
00062 };
00063 
00064 
00065 #endif  // ! LINEARRECOGNISER_H

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